The impact of biases in the tropical South Pacific and near the Agulhaus Current on the large-scale Southern Hemisphere circulation

2020 ◽  
Author(s):  
Chaim Garfinkel ◽  
Ian White ◽  
Edwin Gerber ◽  
Martin Jucker
Keyword(s):  
Southern Hemisphere ◽  
General Circulation Model ◽  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
South Pacific ◽  
Cmip5 Models ◽  
Stationary Waves ◽  
Model Bias ◽  
Intermediate Complexity

<p>A common model bias in comprehensive climate models used in climate assessements such as the Coupled Model Intercomparison Project is a double inter-tropical convergence, with excessive precipitation in the tropical eastern South Pacific. In addition, the current generation of climate models cannot adequately resolve the dynamics of the Agulhas Current, and in particular the relative fraction of the Current that leaks into the Atlantic as opposed to retroflecting back into the Indian Ocean. The intermodel spread in the magnitude of the double ITCZ bias is   significantly correlated with the strength and phasing of   SH stationary waves in the CMIP archive, with models with a smaller bias generally showing more realistic stationary waves. An intermediate complexity moist General Circulation Model is used to demonstrate the causality of this connection: by fluxing heat out of  the tropical South Pacific Ocean, we can capture the  responses seen in CMIP5 models.  Finally, the same intermediate complexity moist General Circulation Model is used to demonstrate that an overly diffuse Agulhas leads to an equatorward shift of the Southern Hemisphere jet by more than  3degrees, and indeed an overly equatorward Southern Hemisphere jet is a common model bias in most CMIP5 models.</p>

scholarly journals Cloud Vertical Distribution across Warm and Cold Fronts in CloudSat–CALIPSO Data and a General Circulation Model

2010 ◽  
Vol 23 (12) ◽  
pp. 3397-3415 ◽  
Author(s):  
Catherine M. Naud ◽  
Anthony D. Del Genio ◽  
Mike Bauer ◽  
William Kovari
Keyword(s):  
Relative Humidity ◽  
Southern Hemisphere ◽  
General Circulation Model ◽  
General Circulation ◽  
Cloud Cover ◽  
Climate Models ◽  
Storm Track ◽  
Circulation Model ◽  
Global Climate Models ◽  
Cold Fronts

Abstract Cloud vertical distributions across extratropical warm and cold fronts are obtained using two consecutive winters of CloudSat–Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations and National Centers for Environmental Prediction reanalysis atmospheric state parameters over the Northern and Southern Hemisphere oceans (30°–70°N/S) between November 2006 and September 2008. These distributions generally resemble those from the original model introduced by the Bergen School in the 1920s, with the following exceptions: 1) substantial low cloudiness, which is present behind and ahead of the warm and cold fronts; 2) ubiquitous high cloudiness, some of it very thin, throughout the warm-frontal region; and 3) upright convective cloudiness near and behind some warm fronts. One winter of GISS general circulation model simulations of Northern and Southern Hemisphere warm and cold fronts at 2° × 2.5° × 32 levels resolution gives similar cloud distributions but with much lower cloud fraction, a shallower depth of cloudiness, and a shorter extent of tilted warm-frontal cloud cover on the cold air side of the surface frontal position. A close examination of the relationship between the cloudiness and relative humidity fields indicates that water vapor is not lifted enough in modeled midlatitude cyclones and this is related to weak vertical velocities in the model. The model also produces too little cloudiness for a given value of vertical velocity or relative humidity. For global climate models run at scales coarser than tens of kilometers, the authors suggest that the current underestimate of modeled cloud cover in the storm track regions, and in particular the 50°–60°S band of the Southern Oceans, could be reduced with the implementation of a slantwise convection parameterization.

scholarly journals The Impact of SST Biases in the Tropical East Pacific and Agulhas Current Region on Atmospheric Stationary Waves in the Southern Hemisphere

2020 ◽  
Vol 33 (21) ◽  
pp. 9351-9374
Author(s):  
Chaim I. Garfinkel ◽  
Ian White ◽  
Edwin P. Gerber ◽  
Martin Jucker
Keyword(s):  
Southern Hemisphere ◽  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Stationary Waves ◽  
Return Current ◽  
Agulhas Current ◽  
East Pacific ◽  
Double Itcz ◽  
The Impact

AbstractClimate models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) vary significantly in their ability to simulate the phase and amplitude of atmospheric stationary waves in the midlatitude Southern Hemisphere. These models also suffer from a double intertropical convergence zone (ITCZ), with excessive precipitation in the tropical eastern South Pacific, and many also suffer from a biased simulation of the dynamics of the Agulhas Current around the tip of South Africa. The intermodel spread in the strength and phasing of SH midlatitude stationary waves in the CMIP archive is shown to be significantly correlated with the double-ITCZ bias and biases in the Agulhas Return Current. An idealized general circulation model (GCM) is used to demonstrate the causality of these links by prescribing an oceanic heat flux out of the tropical east Pacific and near the Agulhas Current. A warm bias in tropical east Pacific SSTs associated with an erroneous double ITCZ leads to a biased representation of midlatitude stationary waves in the austral hemisphere, capturing the response evident in CMIP models. Similarly, an overly diffuse sea surface temperature gradient associated with a weak Agulhas Return Current leads to an equatorward shift of the Southern Hemisphere jet by more than 3° and weak stationary wave activity in the austral hemisphere. Hence, rectification of the double-ITCZ bias and a better representation of the Agulhas Current should be expected to lead to an improved model representation of the austral hemisphere.

scholarly journals Simulating the mid-Pliocene climate with the MIROC general circulation model: experimental design and initial results

2011 ◽  
Vol 4 (4) ◽  
pp. 1035-1049 ◽  
Author(s):  
W.-L. Chan ◽  
A. Abe-Ouchi ◽  
R. Ohgaito
Keyword(s):  
Experimental Design ◽  
Boundary Conditions ◽  
General Circulation Model ◽  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Sea Surface ◽  
Future Climate Change ◽  
Model Intercomparison ◽  
Initial Results

Abstract. Recently, PlioMIP (Pliocene Model Intercomparison Project) was established to assess the ability of various climate models to simulate the mid-Pliocene warm period (mPWP), 3.3–3.0 million years ago. We use MIROC4m, a fully coupled atmosphere-ocean general circulation model (AOGCM), and its atmospheric component alone to simulate the mPWP, utilizing up-to-date data sets designated in PlioMIP as boundary conditions and adhering to the protocols outlined. In this paper, a brief description of the model is given, followed by an explanation of the experimental design and implementation of the boundary conditions, such as topography and sea surface temperature. Initial results show increases of approximately 10°C in the zonal mean surface air temperature at high latitudes accompanied by a decrease in the equator-to-pole temperature gradient. Temperatures in the tropical regions increase more in the AOGCM. However, warming of the AOGCM sea surface in parts of the northern North Atlantic Ocean and Nordic Seas is less than that suggested by proxy data. An investigation of the model-data discrepancies and further model intercomparison studies can lead to a better understanding of the mid-Pliocene climate and of its role in assessing future climate change.

scholarly journals Development of the global atmospheric chemistry general circulation model BCC-GEOS-Chem v1.0: model description and evaluation

2020 ◽  
Vol 13 (9) ◽  
pp. 3817-3838
Author(s):  
Xiao Lu ◽  
Lin Zhang ◽  
Tongwen Wu ◽  
Michael S. Long ◽  
Jun Wang ◽  
...  
Keyword(s):  
General Circulation Model ◽  
Atmospheric Chemistry ◽  
Tropospheric Ozone ◽  
General Circulation ◽  
Climate Models ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Circulation Model ◽  
Satellite Observations ◽  
Model Description

Abstract. Chemistry plays an indispensable role in investigations of the atmosphere; however, many climate models either ignore or greatly simplify atmospheric chemistry, limiting both their accuracy and their scope. We present the development and evaluation of the online global atmospheric chemical model BCC-GEOS-Chem v1.0, coupling the GEOS-Chem chemical transport model (CTM) as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model (BCC-AGCM). The GEOS-Chem atmospheric chemistry component includes detailed tropospheric HOx–NOx–volatile organic compounds–ozone–bromine–aerosol chemistry and online dry and wet deposition schemes. We then demonstrate the new capabilities of BCC-GEOS-Chem v1.0 relative to the base BCC-AGCM model through a 3-year (2012–2014) simulation with anthropogenic emissions from the Community Emissions Data System (CEDS) used in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The model captures well the spatial distributions and seasonal variations in tropospheric ozone, with seasonal mean biases of 0.4–2.2 ppbv at 700–400 hPa compared to satellite observations and within 10 ppbv at the surface to 500 hPa compared to global ozonesonde observations. The model has larger high-ozone biases over the tropics which we attribute to an overestimate of ozone chemical production. It underestimates ozone in the upper troposphere which is likely due either to the use of a simplified stratospheric ozone scheme or to biases in estimated stratosphere–troposphere exchange dynamics. The model diagnoses the global tropospheric ozone burden, OH concentration, and methane chemical lifetime to be 336 Tg, 1.16×106 molecule cm−3, and 8.3 years, respectively, which is consistent with recent multimodel assessments. The spatiotemporal distributions of NO2, CO, SO2, CH2O, and aerosol optical depth are generally in agreement with satellite observations. The development of BCC-GEOS-Chem v1.0 represents an important step for the development of fully coupled earth system models (ESMs) in China.

Developing a data-driven ocean model

2020 ◽  
Author(s):  
Rachel Furner ◽  
Peter Haynes ◽  
Dan Jones ◽  
Dave Munday ◽  
Brooks Paige ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
General Circulation Model ◽  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Geophysical Research ◽  
Weather And Climate

<p>The recent boom in machine learning and data science has led to a number of new opportunities in the environmental sciences. In particular, climate models represent the best tools we have to predict, understand and potentially mitigate climate change, however these process-based models are incredibly complex and require huge amounts of high-performance computing resources. Machine learning offers opportunities to greatly improve the computational efficiency of these models.</p><p>Here we discuss our recent efforts to reduce the computational cost associated with running a process-based model of the physical ocean by developing an analogous data-driven model. We train statistical and machine learning algorithms using the outputs from a highly idealised sector configuration of general circulation model (MITgcm). Our aim is to develop an algorithm which is able to predict the future state of the general circulation model to a similar level of accuracy in a more computationally efficient manner.</p><p>We first develop a linear regression model to investigate the sensitivity of data-driven approaches to various inputs, e.g. temperature on different spatial and temporal scales, and meta-variables such as location information. Following this, we develop a neural network model to replicate the general circulation model, as in the work of Dueben and Bauer 2018, and Scher 2018.</p><p>We present a discussion on the sensitivity of data-driven models and preliminary results from the neural network based model.</p><p> </p><p><em>Dueben, P. D., & Bauer, P. (2018). Challenges and design choices for global weather and climate models based on machine learning. Geoscientific Model Development, 11(10), 3999-4009.</em></p><p><em>Scher, S. (2018). Toward Data‐Driven Weather and Climate Forecasting: Approximating a Simple General Circulation Model With Deep Learning. Geophysical Research Letters, 45(22), 12-616.</em></p>

scholarly journals Improved Simulation of the Antarctic Stratospheric Final Warming by Modifying the Orographic Gravity Wave Parameterization in the Beijing Climate Center Atmospheric General Circulation Model

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 576
Author(s):  
Yixiong Lu ◽  
Tongwen Wu ◽  
Xin Xu ◽  
Li Zhang ◽  
Min Chu
Keyword(s):  
Gravity Wave ◽  
General Circulation Model ◽  
General Circulation ◽  
Climate Models ◽  
Atmospheric General Circulation Model ◽  
Circulation Model ◽  
Wave Drag ◽  
Atmospheric General Circulation ◽  
Stratospheric Final Warming ◽  
The Antarctic

The Antarctic stratospheric final warming (SFW) is usually simulated with a substantial delay in climate models, and the corresponding temperatures in austral spring are lower than observations, implying insufficient stratospheric wave drag. To investigate the role of orographic gravity wave drag (GWD) in modeling the Antarctic SFW, in this study the orographic GWD parameterization scheme is modified in the middle-atmosphere version of the Beijing Climate Center Atmospheric General Circulation Model. A pair of simulations are conducted to compare two orographic GWD schemes in simulating the breakdown of the stratospheric polar vortex over Antarctica. The control simulation with the default orographic GWD scheme exhibits delayed vortex breakdown and the cold-pole bias seen in most climate models. In the simulation with modified orographic GWD scheme, the simulated vortex breaks down earlier by 8 days, and the associated cold-pole bias is reduced by more than 2 K. The modified scheme provides stronger orographic GWD in the lower stratosphere, which drives an accelerated polar downwelling branch of the Brewer–Dobson circulation and, in turn, produces adiabatic warming. Our study suggests that modifying orographic GWD parameterizations in climate models would be a valid way of improving the SFW simulation over Antarctica.

scholarly journals Sensitivity of an atmospheric general circulation model to the parameterization of leads in sea ice

1997 ◽  
Vol 25 ◽  
pp. 96-101 ◽  
Author(s):  
Gregory M. Flato ◽  
David Ramsden
Keyword(s):  
Sea Ice ◽  
General Circulation Model ◽  
General Circulation ◽  
Climate Models ◽  
Atmospheric General Circulation Model ◽  
Circulation Model ◽  
Open Water ◽  
Arctic Sea Ice ◽  
Atmospheric General Circulation ◽  
Hemisphere Winter

Open-water leads in sea ice dominate the exchange of heat between the ocean and atmosphere in ice-covered regions, and so must be included in climate models. A parameterization of leads used in one such model is compared to observations and the results of a detailed Arctic sea-ice model. Such comparisons, however, are hampered by the errors in observed lead fraction, but the parameterization appears to compare better in winter than in summer. Simulations with an atmospheric general circulation model (AGCM), using prescribed sea-surface temperatures and ice extent, are used to illustrate the effect of parameterized lead fraction on atmospheric climate, and so provide some insight into the importance of improved lead-fraction parameterizations and observations. The effect of leads in the AGCM is largest in Northern Hemisphere winter, with zonal mean surface-air temperatures over ice increasing by up to 5 K when lead fraction is increased from 1% to near 5%. The effect of leads on sensible heat loss in winter is more important than the effect on radiative heat gain in summer. No significant effect on sea-level pressure, and hence on atmospheric circulation, is found, however. Indirect effects, due to feedbacks between the atmosphere and ice thickness and extent, were not included in these simulations, but could amplify the response.

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